Opportunistic adjustable rate cross-ambiguity function geolocation

ABSTRACT

Methods and systems for dynamically modifying a sampling operation of a sensor. The method includes obtaining a dynamically changing transmission characteristic based on an available channel bandwidth parameter. The dynamically changing transmission characteristic includes at least one of a sample rate, a time period, or a spectral bandwidth. The method further includes updating the sampling operation of the sensor based on the dynamically changing transmission characteristic. The method further includes measuring signal energy at a location of the sensor. The method further includes sampling the signal energy using the sampling operation to obtain sampled data. The method further includes providing the sampled data to a processing entity configured to analyze the data using a dynamically updated cross-ambiguity function.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.16/130,534 filed on Sep. 13, 2018, entitled “Opportunistic AdjustableRate Cross-Ambiguity Function Geolocation,” and which application isexpressly incorporated herein by reference in its entirety.

BACKGROUND Background and Relevant Art

Geolocation of signal sources, such as radio-frequency (RF) sources andthe like, allows for the location of a signal source based on itsemitted signal. Digital signal processing techniques exist that performgeolocation by analyzing sampled data. One such technique uses across-ambiguity function (CAF). Typical systems for performing CAFgeolocation have multiple sampling platforms or sensors that gather dataat the different sampling platforms or sensors. By providing the CAFwith two or more sets of this sampled data, the time difference ofarrival (TDOA) and frequency difference of arrival (FDOA) between thesets of sampled data can be found. The location of the signal source canbe determined from the TDOA and FDOA.

While CAF can provide high-quality geolocation, one disadvantage is thatCAF has high bandwidth requirements for communication between thedifferent platforms that capture the sample data, including transmissionof the sample data. When the available channel bandwidth is restrictedor varies, the performance of CAF geolocation can suffer.

The subject matter claimed herein is not limited to embodiments thatsolve any disadvantages or that operate only in environments such asthose described above. Rather, this background is only provided toillustrate one exemplary technology area where some embodimentsdescribed herein may be practiced.

BRIEF SUMMARY

One embodiment illustrated herein includes a method for dynamicallymodifying a sampling operation of a sensor. The method includesobtaining a dynamically changing transmission characteristic based on anavailable channel bandwidth parameter. The dynamically changingtransmission characteristic includes at least one of a sample rate, atime period, or a spectral bandwidth. The method further includesupdating the sampling operation of the sensor based on the dynamicallychanging transmission characteristic. The method further includesmeasuring signal energy at a location of the sensor. The method furtherincludes sampling the signal energy using the sampling operation toobtain sampled data. The method further includes providing the sampleddata to a processing entity configured to analyze the data using adynamically updated cross-ambiguity function.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

Additional features and advantages will be set forth in the descriptionwhich follows, and in part will be obvious from the description, or maybe learned by the practice of the teachings herein. Features andadvantages of the invention may be realized and obtained by means of theinstruments and combinations particularly pointed out in the appendedclaims. Features of the present invention will become more fullyapparent from the following description and appended claims, or may belearned by the practice of the invention as set forth hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features can be obtained, a more particular descriptionof the subject matter briefly described above will be rendered byreference to specific embodiments which are illustrated in the appendeddrawings. Understanding that these drawings depict only typicalembodiments and are not therefore to be considered to be limiting inscope, embodiments will be described and explained with additionalspecificity and detail through the use of the accompanying drawings inwhich:

FIG. 1 illustrates a sensor device.

FIG. 2 illustrates a processing center.

FIG. 3 illustrates a geolocation environment.

FIG. 4 illustrates a method for dynamically updating a CAF anddetermining the location of a signal source.

FIG. 5 illustrates a method for dynamically updating a samplingoperation in a sensor.

DETAILED DESCRIPTION

The following discussion now refers to a number of methods and methodacts that may be performed, as well as a system capable of performingthe methods and other operations. Although the method acts may bediscussed in a certain order or illustrated in a flow chart as occurringin a particular order, no particular ordering is required unlessspecifically stated, or required because an act is dependent on anotheract being completed prior to the act being performed.

Referring now to FIG. 1, a sensor 100 is illustrated. In someembodiments, the sensor 100 is in a fixed position. In some embodiments,the sensor 100 is mobile or capable of being moved. For example, in someembodiments, the sensor 100 is part of a mobile device such as a smartphone, tablet, laptop, or similar devices. In other embodiments, thesensor 100 is mounted on or integrated in a drone or vehicle, such as anaircraft, boat, or car.

The sensor 100 has a sensing element 101 for measuring the environmentwhere the sensor is located. In some embodiments, the sensing element101 is an antenna. In some embodiments, the sensing element 101 is anelement configured to measure RF energy.

The sensor 100 also has a data acquisition unit 102 for converting thesensing element 101's measurements into digital information. In someembodiments, the data acquisition unit 102 performs a sampling operationon the measurements. In some embodiments, the data acquisition unit 102converts the measurements into spectral measurements in the frequencydomain.

The sensor 100 also has processor(s) 103 and computer-readable media104. The processor(s) 103 execute instructions on the computer-readablemedia 104. In some embodiments, the processor(s) 103 control the sensingelement 101. In some embodiments, the processor(s) 103 control the dataacquisition unit.

In some embodiments, the computer-readable media 104 containsinstructions for the processor(s) 103 obtaining a dynamically changingtransmission characteristic based on an available channel bandwidthparameter. In some embodiments, the dynamically changing transmissioncharacteristic comprises at least one of a sample rate, a time period,or a spectral bandwidth. In some embodiments, the time period describesa length of time over which data are to be gathered. In someembodiments, the time period is defined by specific starting andstopping times. In some embodiments, the spectral bandwidth is one ormore spectral regions over which data are to be gathered. In someembodiments, this is a defined by a first frequency and a secondfrequency, with the spectral bandwidth being the frequencies between thefirst frequency and the second frequency.

In some embodiments, the computer-readable media 104 containsinstructions for the processor(s) 103 calculating or otherwisedetermining the dynamically changing transmission characteristic. Insome embodiments, calculating the dynamically changing transmissioncharacteristic comprises calculating or otherwise determining at leastone of the sample rate, time period or spectral bandwidth. In someembodiments, obtaining the dynamically changing transmissioncharacteristic involves receiving the dynamically changing transmissioncharacteristic from another source, device, or system.

In some embodiments, the computer-readable media 104 containsinstructions for the processors(s) 103 updating how the sensing element101 measures the signal energy at the sensor 100. In some embodiments,the computer-readable media 104 contains instructions for theprocessors(s) 103 updating a sampling operation performed on themeasurements. In some embodiments, updating the sampling operationcomprises changing the at least one of the sample rate, the time period,or the spectral bandwidth of the sampling operation. In someembodiments, the computer-readable media 104 contains instructions forthe processors(s) 103 measuring data with the sensing element 101. Insome embodiments, the computer-readable media 104 contains instructionsfor the processors(s) 103 sampling data with the data acquisition unit102, producing a set of sampled data comprising one or more samples.

In some embodiments, updating how the sensing element 101 measures theenvironment or the sampling operation is performed repeatedly ordynamically over time. In some embodiments, the updating is performedbased on the dynamically changing transmission characteristic. In someembodiments, the repeated or dynamic updating changes as the dynamicallychanging transmission characteristic changes.

In some embodiments, the computer-readable media 104 containsinstructions for the processor(s) 103 providing the measured and sampleddata to a processing element configured to analyze the data using a CAF.

In some embodiments, the sensor 100 includes a transmitter/receiver 105for transmitting and receiving data to other devices. In someembodiments, the computer-readable media 104 contains instructions forthe processor(s) 103 transmitting the measured and sampled data to aprocessing element using the transmitter/receiver 105.

In some embodiments, the sensor 100 is configured to measure theavailable bandwidth between the sensor 100 and another device. In someembodiments, the computer-readable media 104 contains instructions forthe processor(s) 103 making such measurements. In some embodiments, themeasured available bandwidth is the available channel bandwidthparameter. In some embodiments, the available channel bandwidthparameter is provided to the sensor 100. In some embodiments, thecomputer-readable media 104 contains instructions for the processor(s)103 receiving the available channel bandwidth parameter from anotherdevice using the transmitter/receiver 105.

FIG. 2 illustrates a processing center 200 for providing processingoperations in a network. The processing center 200 has processor(s) 201for executing instructions contained on computer-readable media 202. Insome embodiments, the processing center has a transmitter/receiver 203.

The computer-readable media 202 contains instructions for theprocessors(s) 201 accessing sampled data. In some embodiments, thesampled data are multiple sets of sampled data, each sampled at a samplerate over a time period and across a spectral bandwidth. For example,the sampled data can be the data measured by a sensor 100 as describedabove. In some embodiments, the sampled data are accessed from memory.In some embodiments, the sampled data are received from other sources bythe transmitter/receiver 203. In some embodiments, the sampled datacomprises multiple sets of data, with different data sets being accessedin different ways. For example, one set of sampled data might beaccessed locally from memory and other sets of sampled data might bereceived from other sources by the transmitter receiver 203.

The computer-readable media 202 contains instructions for theprocessors(s) 201 applying a CAF to sampled data of a signal todetermine the location of the source of the signal. In some embodiments,the computer-readable media 202 also contains instructions for updatingthe CAF based on the sample rate, time period, and spectral bandwidth ofone or more sets of the sampled data. In some embodiments, the sampleddata are sampled at one or more sample rates, time periods, and spectralbandwidths. In some embodiments, the CAF is updated based on a dynamictransmission characteristic and the sampled data accessed by theprocessing center 200 is also sampled according to the dynamictransmission characteristic. In some embodiments, updating the CAF basedon the dynamic transmission characteristic is performed dynamically asthe dynamic transmission characteristic changes.

In some embodiments, the transmitter/receiver 203 is used to communicatewith other devices. In some embodiments, those devices are part of anetwork with the processing element 200. In some embodiments, thetransmitter/receiver 203 also provides user access to processing element200 or a network to which processing element 200 is connected.

FIG. 3 illustrates a geolocation environment 300. The geolocationenvironment 300 shows a setting where a signal source 320 transmits asignal 325. The environment 300 also includes a geolocation system 310,which is made up of one or more sensors 100, shown as sensors 100 a, 100b, 100 c, 100 d, and 100 e, as well as a processing center 200.Geolocation system 310 is exemplary, but should not be seen asdisclosing a requirement or limitation on the number of sensors or theirphysical arrangement. In some embodiments, the geolocation environment300 also includes interference source(s) 330.

The geolocation system 310 is configured to determine the location ofthe signal source 320 present in the geolocation environment bymeasuring and sampling the signal 325 with the sensors 100 a, 100 b, 100c, 100 d, and 100 e, transmitting or otherwise providing that data tothe processing center 200, and then applying a CAF to the sampled datain the processing center 200.

Each sensor 100 a, 100 b, 100 c, 100 d, and 100 e has a channel 315 a,315 b, 315 c, 315 d, and 315 e that represents a connection between thespecific sensor and the processing center 200. In some embodiments, thechannel is a wireless or RF communication channel. In some embodiments,one or more of the sensors 100 a, 100 b, 100 c, 100 d, and 100 e areentities in a network. In some embodiments, one or more of the sensors100 a, 100 b, 100 c, 100 d, and 100 e are integrated into, part of, orotherwise connected to network entities. In some embodiments, thenetwork entities are part of an ad-hoc network.

In some embodiments, the processing center 200 is co-located with asensor 100. For example, sensor 100 b and processing center 200 can bedirectly connected or integrated. In such embodiments, the channelbetween the sensor 100 and the processing center 200 is a connectionbetween the devices or within the device which both the sensor 100 andthe processing center 200 are integrated. In some embodiments, theprocessor(s) 103 and the processor(s) 201 as described above areintegrated or otherwise the same processor(s). In some embodiments, thecomputer-readable media 104 and computer-readable media 202 areintegrated or otherwise the same computer-readable media.

In some embodiments, the processing center 200 can be moved amongst thesensors 100 a, 100 b, 100 c, 100 d, and 100 e. In some embodiments, theprocessing center movement is achieved through software. For example, asdiscussed above, the processors and computer-readable media may becommon between the processing center and the sensors or the sensor maybe integrated into a device with other resources capable of performingthe processing center 200 functions.

In some embodiments, the processing center 200 is moved based on thebandwidth available in the communications channels 315 a, 315 b, 315 c,315 d, and 315 e. In some embodiments, the processing center 200 ismoved to improve the bandwidth available in channels 315 a, 315 b, 315c, 315 d, and 315 e. For example, the processing center 200 might bemoved to a sensor such that the minimum bandwidth among all the channels315 a, 315 b, 315 c, 315 d, and 315 e is maximized.

The geolocation system 310 works by measuring the signal 325 at thesensors 100 a, 100 b, 100 c, 100 d, and 100 e. As described above forsensor 100, the signal 325 is measured, sampled at a sample rate over atime period and across a spectral bandwidth. Each of the sensors 100 a,100 b, 100 c, 100 d, and 100 e measures and samples such that there isat least one sample or set of samples that overlap in the time periodover and spectral bandwidth across which the samples were gathered. Insome embodiments, the sampled data from each of the sensors 100 a, 100b, 100 c, 100 d, and 100 e exactly overlap. For example, each set ofsampled data begins at the same first time and first spectral frequencyand ends at the same second time and second spectral frequency. In otherembodiments, the sampled data from each of the sensor 100 a, 100 b, 100c, 100 d, and 100 e only partially overlap. For example, each set ofsampled data includes data sampled over a time period and across aspectral bandwidth, but one or more sets of the sampled data alsoinclude data sampled outside of the time period and spectral bandwidth.

After measuring and sampling the signal 325, the sensors 100 a, 100 b,100 c, 100 d, and 100 e provide sets of sampled data to the processingcenter 200 using the corresponding communications channel 315 a, 315 b,315 c, 315 d, or 315 e. In some embodiments, the communications channel315 a, 315 b, 315 c, 315 d, or 315 e is a wireless or RF communicationschannel. In some embodiments, the communications channel 315 a, 315 b,315 c, 315 d, or 315 e corresponds to a local memory access, such asreading data from computer-readable media 104 or 202.

The processing center 200 uses a CAF on the sampled data to determine aTDOA and FDOA between two or more of the sets of sampled data. This canthen be used to determine the location of the signal source.

As discussed above for sensor 100, the sensors 100 a, 100 b, 100 c, 100d, and 100 e of the geolocation system 310 can be fixed, stationary, ormobile. Likewise, processing center 200 can be fixed, stationary, ormobile. In some embodiments, the sensors 100 a, 100 b, 100 c, 100 d, and100 e form an ad hoc network. While FIG. 3 shows signal source 320 andinterference source(s) 330 as somewhat external to the geolocationsystem 310, due to the distributed and possibly mobile nature of thesensors 100 a, 100 b, 100 c, 100 d, and 100 e, as well as processingcenter 200, the signal source 320 or interference sources 330 may infact be physically located between or among the elements of thegeolocation system 310. Nothing in FIG. 3 should be seen as limiting therelative physical locations of the signal source 320, the interferencesource(s) 330, and the geolocation system 310 with respect to oneanother.

Due to the physics of the actual geolocation environment 300, includingthe impact of interference source(s) 330, in some embodiments, theavailable bandwidth and other properties of one or more of thecommunications channels 315 a, 315 b, 315 c, 315 d, and 315 e changewith time. As was discussed above and as will be discussed further inthe methods below, the geolocation system 310 is configured todynamically update the sensing operations performed by sensors 100 a,100 b, 100 c, 100 d, and 100 e and geolocation calculations performed bythe processing center 200. In some embodiments, calculations areperformed at a central location to determine how to dynamically updatethe geolocation system 310. For example, in some embodiments, theprocessing center 200 performs the calculations. In other embodiments,the calculations may be performed externally and be provided to thegeolocation system 310. In some embodiments, the calculations areperformed in a variety of locations. For example, in some embodiments,each of the sensors 100 a, 100 b, 100 c, 100 d, and 100 e performs partof the calculations, while the processing center 200 performs theremainder.

FIG. 4 illustrates a geolocation method 400 for determining the locationof a signal source. In some embodiments, the geolocation method 400 isperformed by the geolocation system 310 depicted in FIG. 3. In someembodiments, the geolocation method 400 is applied dynamically orrepeatedly to adjust portions of the geolocation system 310 of FIG. 3 toaccount for changes in the communications channels 315 a, 315 b, 315 c,315 d, or 315 e. For example, referring again to FIG. 3, if one or moreof sensors 100 a, 100 b, 100 c, 100 d, and 100 e moves or interferencesource(s) 330 is/are time varying, the channel parameters, includingavailable bandwidth, may vary. By applying geolocation method 400 atdifferent times, the geolocation method is updated to account forchanges in the channel. In some embodiments, different times mean aperiodic occurrence, such as every second or after every time period ofa sampling operation. In some embodiments, different times aredetermined by measuring or detecting changes in communications channels315 a, 315 b, 315 c, 315 d, and 315 e depicted in FIG. 3.

The geolocation method 400 includes obtaining the available channelbandwidth parameter (Act 402). In some embodiments, this is performed bymeasuring an available channel bandwidth between a sensor 100 and aprocessing center 200. For example, referring to FIG. 3, in someembodiments, the channel bandwidth available in communications channels315 a, 315 b, 315 c, 315 d, and 315 e are measured to find the availablechannel bandwidth between sensors 100 a, 100 b, 100 c, 100 d, and 100 eand processing center 200. In some embodiments, the available channelbandwidth parameter is the bandwidth in more than one of these channels.For example, in the geolocation system 310 shown in FIG. 3, in someembodiments, the available channel bandwidth parameter is the availablechannel bandwidths in all of the communications channels 315 a, 315 b,315 c, 315 d, and 315 e. In some embodiments, sensors 100 a, 100 b, 100c, 100 d, and 100 e measure the available channel bandwidth. In someembodiments, the processing center measures the available channelbandwidth.

In some embodiments, the available channel bandwidth parameter isreceived from an external source. For example, in some embodiments, auser selects a value for the available channel bandwidth parameter. Insome embodiments, the available channel bandwidth parameter iscalculated. For example, in the geolocation system 310 shown in FIG. 3,when the bandwidth in the communications channels 315 a, 315 b, 315 c,315 d, and 315 e is measured or provided, in some embodiments, theavailable channel bandwidth parameter is calculated as a value based onthose bandwidths, such as the minimum bandwidth of all the bandwidths.

In some embodiments, the available channel bandwidth parameter includesother values, such as a spectral target band. The spectral target bandis bandwidth in which a signal of interest is or is expected to belocated. In some embodiments, the available channel bandwidth includes atarget time period, which is a time period over which a signal ofinterest is to be measured.

Geolocation method 400 further includes obtaining a dynamically changingtransmission characteristic based on the available channel bandwidthparameter (Act 404). In some embodiments, the dynamically changingtransmission characteristic is at least one of a sample rate, a timeperiod, or a spectral bandwidth. In some embodiments, the dynamicallychanging transmission characteristic is obtained by selecting at leastone of a sample rate, a time period for sampling, or a spectralbandwidth over which to sample such that a data transmission rate can bemaintained when transmitting the sampled data. For example, for a fixedsample rate and spectral bandwidth, a certain time period over whichsamples are gathered is required to maintain a predeterminedtransmission rate in a channel between two devices, such as sensor 100 aand processing center 200 depicted in FIG. 3. Based on the availablechannel bandwidth parameter, a certain value for time period isselected.

In some embodiments, the dynamically changing transmissioncharacteristic uses the available channel bandwidth parameter todetermine the spectral bandwidth over which to measure data. Forexample, in embodiments where the available channel bandwidth parameterincludes a spectral target band, the spectral bandwidth chosen for thedynamically changing transmission characteristic is chosen to include atleast a part of the spectral target band.

In some embodiments, the dynamically changing transmissioncharacteristic uses the available channel bandwidth parameter todetermine the time period over which to measure data. For example, inembodiments where the available channel bandwidth parameter includes atarget time period, the time period chosen for the dynamically changingtransmission characteristic is chosen to include at least a part of thetarget time period.

Geolocation method 400 further includes receiving overlapping sampleddata (Act 406). In some embodiments, the sampled data are transmitted bya plurality of sensors, such as sensors 100 a, 100 b, 100 c, 100 d, and100 e depicted in FIG. 3. More than one set of the sampled data providedby the plurality of sensors include at least a part of a signal ofinterest emitted by a signal source, such as signal 325 emitted bysignal source 320 depicted in FIG. 3. Each sensor provides a set ofsampled data that includes one or more samples gathered at a sample rateover a time period and across a spectral bandwidth. Each set of sampleddata overlaps in time period and spectral bandwidth such that each setof sampled data includes or spans common values. In some embodiments,the sets of sample data overlap completely. In some embodiments, thismeans that all of the sets of sample data include sample points in theexact same time period and spectral bandwidth, although not necessarilyat the same sample rate. In some embodiments, each set of sample data issampled with the same sample rate over the same time period and acrossthe same spectral bandwidth.

In some embodiments, geolocation method 400 also includes providing thedynamically changing transmission characteristic to the plurality ofsensors. In some embodiments, the dynamically changing transmissioncharacteristic is provided to the plurality of sensors so that theplurality of sensors can update their sampling operation and providesampled data that is sampled based on the dynamically changingtransmission characteristic. In some embodiments, the sensors updatetheir sampling operation and provide the sampled data according tosampling operation update method 500, described below.

Geolocation method 400 also includes updating a CAF based on thedynamically changing transmission characteristic (Act 408). In someembodiments, this involves updating the CAF to analyze based on at leastone sample rate, at least one time period, and at least one spectralbandwidth contained in or determined from the dynamically changingtransmission characteristic.

In some embodiments, the sets of sampled data received in act 406 aresampled at the same at least one sample rate over the same at least onetime period and across the same at least one spectral bandwidth as thoseused to update the CAF. For example, if the CAF is updated to analyzeusing a first sample rate, a second sample rate, a first time period, asecond time period, a first spectral bandwidth, and a second spectralbandwidth, a first set of sampled data are sampled at the first samplerate over the first time period and across the first spectral bandwidthand a second set of sampled data are sampled at the second sample rateover the second time period and across the second spectral bandwidth.

In some embodiments, at least one set of sampled data received in act406 is sampled at a first sample rate over a first time period andacross a first spectral bandwidth and the CAF is updated based on atleast one sample rate, at least one time period, and at least onespectral bandwidth, and where further at least one of the first samplerate, first time period, or first spectral bandwidth does not match theat least one sample rate, the at least one time period, and the at leastone spectral bandwidth, respectively. In some embodiments, the at leastone set of sampled data is modified to change at least one of the firstsample rate, the first time period, or the first spectral bandwidth. Insome embodiments, the at least one set of sampled data is modified suchthat it can be analyzed in the CAF. For example, in some embodiments, ifthe first sample rate of the at least one set of sampled data does notmatch the at least one sample rate, the at least one set of sample datais upsampled or downsampled to match one of the at least one samplerates used by the CAF.

The geolocation method 400 further includes determining the location ofa signal source by applying the updated CAF to the overlapping sampledata (Act 410). In some embodiments, this is performed on two or moresets of sample data that overlap in the time period and spectralbandwidth over which the samples were gathered. In some embodiments, theCAF is applied to different sets of sampled data in separate operationsand the results are combined or compared to determine the location ofthe signal source. In some embodiments, CAF is performed on all the setsof sampled data at once.

FIG. 5 illustrates a sampling operation update method 500 for updatingthe sampling operation of a sensor, measuring data, and sampling themeasurements using the updated sampling operation. In some embodiments,the method is used to update the sampling operations of sensors 100 a,100 b, 100 c, 100 d, and 100 e depicted in FIG. 3.

The sampling operation update method 500 begins by obtaining theavailable channel bandwidth parameter (Act 502). In some embodiments,this is performed by measuring an available channel bandwidth between asensor 100 and a processing center 200, depicted in FIG. 3. For example,in the geolocation system 310 shown in FIG. 3, in some embodiments, thechannel bandwidth available in communications channel 315 a, 315 b, 315c, 315 d, and 315 e is measured to find the available channel bandwidthbetween sensors 100 a, 100 b, 100 c, 100 d, and 100 e and processingcenter 200. In some embodiments, the available channel bandwidthparameter is the bandwidth in more than one of these channels. Forexample, in some embodiments, the available channel bandwidth parameteris the available channel bandwidths in all of the communicationschannels 315 a, 315 b, 315 c, 315 d, and 315 e. In some embodiments,sensors 100 a, 100 b, 100 c, 100 d, and 100 e measure the availablechannel bandwidth. In some embodiments, another device, such asprocessing center 200 depicted in FIG. 3, measures the available channelbandwidth.

In some embodiments, the available channel bandwidth parameter isreceived from an external source. For example, in some embodiments, auser selects a value for the available channel bandwidth parameter. Insome embodiments, the available channel bandwidth parameter iscalculated. For example, in some embodiments, the bandwidth in thecommunications channels 315 a, 315 b, 315 c, 315 d, and 315 e of FIG. 3is measured or provided and the available channel bandwidth parameter isselected based on those bandwidths, such as the minimum bandwidth of allthe bandwidths.

In some embodiments, the available channel bandwidth parameter includesother values, such as a spectral target band. The spectral target bandis bandwidth in which a signal of interest is or is expected to belocated. In some embodiments, the available channel bandwidth includes atarget time period, which is a time period over which a signal ofinterest is to be measured.

Sampling operation update method 500 also includes obtaining adynamically changing transmission characteristic based on the availablechannel bandwidth (Act 504) In some embodiments, the dynamicallychanging transmission characteristic is at least one of a sample rate, atime period, or a spectral bandwidth. In some embodiments, thedynamically changing transmission characteristic is obtained byselecting at least one of a sample rate, a time period for sampling, ora spectral bandwidth over which to sample such that a data transmissionrate can be maintained when transmitting the sampled data. For example,for a fixed sample rate and spectral bandwidth, a certain time periodover which samples are gathered is required to maintain a predeterminedtransmission rate in a channel between two devices, such as sensor 100 aand processing center 200 depicted in FIG. 3. Based on the availablechannel bandwidth parameter, a certain value for time period isselected.

In some embodiments, the dynamically changing transmissioncharacteristic uses the available channel bandwidth parameter todetermine the spectral bandwidth over which to measure data. Forexample, in embodiments where the available channel bandwidth parameterincludes a spectral target band, the spectral bandwidth chosen for thedynamically changing transmission characteristic is chosen to include atleast a part of the spectral target band.

In some embodiments, the dynamically changing transmissioncharacteristic uses the available channel bandwidth parameter todetermine the time period over which to measure data. For example, inembodiments where the available channel bandwidth parameter includes atarget time period, the time period chosen for the dynamically changingtransmission characteristic is chosen to include at least a part of thetarget time period.

The sampling operation update method 500 also includes updating asampling operation based on the dynamically changing transmissioncharacteristic (Act 506). In some embodiments, this includes updatingone or more of the parameters of a sampling operation based on thedynamically changing transmission characteristic. The parameters of thesampling operation include sample rate, time period, and spectralbandwidth. For example, when the dynamically changing transmissioncharacteristic includes a second sample rate, updating the samplingoperation includes changing the first sample rate of the samplingoperation to be the second sample rate. In some embodiments, the firstsample rate and second sample rate are the same. In some embodimentswhen the first and second sample rate are the same, updating thesampling operation includes identifying that the first and second samplerates are the same and not updating the first sample rate.

The sampling operation update method also includes measuring signalenergy at the sensor location (Act 508). In some embodiments, measuringsignal energy is performed by a sensor, such as sensors 100 a, 100 b,100 c, 100 d, or 100 e depicted in FIG. 3. In some embodiments, thesensor measures the RF environment at the sensor. In some embodiments,the sensor measures specific bandwidths or frequencies. In someembodiments, those specific bandwidths or frequencies are chosen basedon a signal of interest, such as signal 325 depicted in FIG. 3. In someembodiments, measuring signal energy is performed over a time period,such as the time period in the sampling operation updated in act 506.

The sampling operation update method 500 further includes sampling thesignal energy using the sampling operation (Act 510). In someembodiments, this involves sampling the signal energy measured in act508. In some embodiments, the sampling operation is performed by asensor 100 depicted in FIG. 1 or by sensors such as 100 a, 100 b, 100 c,100 d, and 100 e depicted in FIG. 3.

In some embodiments, the measuring of act 508 is performed by a sensingelement 101 and the sampling operation of act 510 is performed by a dataacquisition unit 102, both depicted in FIG. 1. In some embodiments, themeasured signal energy is only measured by the sensing element 101 andthe sensor 100 directly samples the measured signal energy according toact 510.

In some embodiments, the signal energy is sampled at a sample rate overa time period of the measured signal energy and across a spectralbandwidth of the measured signal energy, as defined in the updatedsampling operation. In some embodiments, the result of the sampling is aset of sampled data that includes one or more samples.

The sampling operation update method 500 also provides sampled data to aprocessing entity configured to analyze the data using a dynamicallyupdated cross-ambiguity function (Act 512). In some embodiments, act 512is performed by a sensor, such as sensor 100 in FIG. 1 or sensors 100 a,100 b, 100 c, 100 d, or 100 e in FIG. 3. In some embodiments, theprocessing entity is the processing center 200 depicted in FIGS. 2 and3. The dynamically updated CAF is updated as described in the acts ofgeolocation method 400 above that relate to updating a CAF.

In some embodiments, the sampled data are transmitted to the processingentity. For example, referring now to FIG. 3, in some embodiments,sensors 100 a, 100 b, 100 c, 100 d, or 100 e transmit sampled data usingtransmitter/receiver 105 to processing center 200. In some embodiments,providing the sampled data to a processing entity is performed bystoring the sampled data in computer-readable memory where theprocessing entity can access the sampled data. As described above, insome embodiments, a sensor 100 a, 100 b, 100 c, 100 d, or 100 e andprocessing center 200 are integrated or directly connected such thatproviding the data to processing center 200 is accomplished byprocessing center 200 directly accessing the computer-readable memorywhere the sampled data are stored.

In some embodiments, sampling operation update method 500 is performedrepeatedly by a sensor, such as sensor 100 in FIG. 1 or sensors 100 a,100 b, 100 c, 100 d, and 100 e in FIG. 3, to dynamically update thesampling operation over time. In some embodiments, sampling operationupdate method 500 is applied dynamically or repeatedly to updateportions of a sampling operation to account for changes in thecommunications channel, such as communications channels 315 a, 315 b,315 c, 315 d, or 315 e depicted in FIG. 3. For example, referring now toFIG. 3, if one or more of sensors 100 a, 100 b, 100 c, 100 d, and 100 emoves or interference source(s) 330 is/are time varying, the channelparameters 315 a, 315 b, 315 c, 315 d, or 315 e, including availablebandwidth, may vary. By applying sampling operation update method 500 atdifferent times, the sampling operation is updated to account forchanges in the channel. In some embodiments, different times means aperiodic occurrence, such as every second or after every time period ofa sampling operation. In some embodiments, different times aredetermined by measuring or detecting changes in communications channel315 a, 315 b, 315 c, 315 d, and 315 e depicted in FIG. 3.

Returning now to FIG. 3, in some embodiments of geolocation system 310,sensors 100 a, 100 b, 100 c, 100 d, and 100 e perform sampling operationupdate method 500. In some embodiments of geolocation system 310,processing center 200 performs geolocation method 400. In someembodiments of geolocation system 310, sensors 100 a, 100 b, 100 c, 100d, and 100 e and processing center 200 perform sampling operation updatemethod 500 and geolocation method 400. In some embodiments, thesemethods are performed repeatedly over time to dynamically update thesampling operation and geolocation calculations based on changingchannel parameters so that the sampling operation update method 500 isupdated to match the performance needs of the CAF used in geolocationmethod 400.

In some embodiments, the dynamically changing transmissioncharacteristic of geolocation method 400 and sampling operation updatemethod 500 are the same. In some embodiments, the available channelbandwidth for sampling operation update method 500 is different for eachof the sensors 100 a, 100 b, 100 c, 100 d, and 100 e, resulting in adifferent dynamically changing transmission characteristic.

Further, the methods may be practiced by a computer system including oneor more processors and computer-readable media such as computer memory.In particular, the computer memory may store computer-executableinstructions that when executed by one or more processors cause variousfunctions to be performed, such as the acts recited in the embodiments.

Embodiments of the present invention may comprise or utilize a specialpurpose or general-purpose computer including computer hardware, asdiscussed in greater detail below. Embodiments within the scope of thepresent invention also include physical and other computer-readablemedia for carrying or storing computer-executable instructions and/ordata structures. Such computer-readable media can be any available mediathat can be accessed by a general purpose or special purpose computersystem. Computer-readable media that store computer-executableinstructions are physical storage media. Computer-readable media thatcarry computer-executable instructions are transmission media. Thus, byway of example, and not limitation, embodiments of the invention cancomprise at least two distinctly different kinds of computer-readablemedia: physical computer-readable storage media and transmissioncomputer-readable media.

Physical computer-readable storage media includes RAM, ROM, EEPROM,CD-ROM or other optical disk storage (such as CDs, DVDs, etc.), magneticdisk storage or other magnetic storage devices, or any other mediumwhich can be used to store desired program code means in the form ofcomputer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer.

A “network” is defined as one or more data links that enable thetransport of electronic data between computer systems and/or modulesand/or other electronic devices. When information is transferred orprovided over a network or another communications connection (eitherhardwired, wireless, or a combination of hardwired or wireless) to acomputer, the computer properly views the connection as a transmissionmedium. Transmissions media can include a network and/or data linkswhich can be used to carry desired program code means in the form ofcomputer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer. Combinationsof the above are also included within the scope of computer-readablemedia.

Further, upon reaching various computer system components, program codemeans in the form of computer-executable instructions or data structurescan be transferred automatically from transmission computer-readablemedia to physical computer-readable storage media (or vice versa). Forexample, computer-executable instructions or data structures receivedover a network or data link can be buffered in RAM within a networkinterface module (e.g., a “NIC”), and then eventually transferred tocomputer system RANI and/or to less volatile computer-readable physicalstorage media at a computer system. Thus, computer-readable physicalstorage media can be included in computer system components that also(or even primarily) utilize transmission media.

Computer-executable instructions comprise, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. The computer-executable instructions may be, forexample, binaries, intermediate format instructions such as assemblylanguage, or even source code. Although the subject matter has beendescribed in language specific to structural features and/ormethodological acts, it is to be understood that the subject matterdefined in the appended claims is not necessarily limited to thedescribed features or acts described above. Rather, the describedfeatures and acts are disclosed as example forms of implementing theclaims.

Those skilled in the art will appreciate that the invention may bepracticed in network computing environments with many types of computersystem configurations, including, personal computers, desktop computers,laptop computers, message processors, hand-held devices, multi-processorsystems, microprocessor-based or programmable consumer electronics,network PCs, minicomputers, mainframe computers, mobile telephones,PDAs, pagers, routers, switches, and the like. The invention may also bepracticed in distributed system environments where local and remotecomputer systems, which are linked (either by hardwired data links,wireless data links, or by a combination of hardwired and wireless datalinks) through a network, both perform tasks. In a distributed systemenvironment, program modules may be located in both local and remotememory storage devices.

Alternatively, or in addition, the functionality described herein can beperformed, at least in part, by one or more hardware logic components.For example, and without limitation, illustrative types of hardwarelogic components that can be used include Field-programmable Gate Arrays(FPGAs), Program-specific Integrated Circuits (ASICs), Program-specificStandard Products (ASSPs), System-on-a-chip systems (SOCs), ComplexProgrammable Logic Devices (CPLDs), etc.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or characteristics. The described embodimentsare to be considered in all respects only as illustrative and notrestrictive. The scope of the invention is, therefore, indicated by theappended claims rather than by the foregoing description. All changeswhich come within the meaning and range of equivalency of the claims areto be embraced within their scope.

What is claimed is:
 1. A method for dynamically modifying a samplingoperation of a sensor, the method comprising: obtaining a dynamicallychanging transmission characteristic based on an available channelbandwidth parameter, the dynamically changing transmissioncharacteristic comprising at least one of a sample rate, a time period,or a spectral bandwidth; updating the sampling operation of the sensorbased on the dynamically changing transmission characteristic; measuringsignal energy at a location of the sensor; sampling the signal energyusing the sampling operation to obtain sampled data; and providing thesampled data to a processing entity configured to analyze the data usinga dynamically updated cross-ambiguity function.
 2. The method of claim1, further comprising obtaining the available channel bandwidthparameter by obtaining an available bandwidth between the sensor and theprocessing entity configured to analyze the data using a cross-ambiguityfunction.
 3. The method of claim 2, wherein obtaining the availablebandwidth between the sensor and the processing entity configured toanalyze the data using a cross-ambiguity function comprises measuringthe available bandwidth.
 4. The method of claim 1, further comprisingobtaining the available channel bandwidth parameter by obtaining abandwidth between a plurality of sensors and the processing entityconfigured to analyze the data using the dynamically updatedcross-ambiguity function.
 5. The method of claim 1, wherein obtainingthe available channel bandwidth parameter comprises receiving a userselected value from an external source.
 6. The method of claim 1,wherein obtaining the available channel bandwidth parameter comprisesreceiving a calculated value based on a minimum of a plurality ofavailable bandwidths of a plurality of communication channels.
 7. Themethod of claim 1, wherein the available channel bandwidth parametercomprises a spectral target band.
 8. The method of claim 1, whereinobtaining the available channel bandwidth parameter comprises receivinga target time period of which a signal of interest is to be measured. 9.The method of claim 1, wherein the dynamically changing transmissioncharacteristic is obtained by selecting at least one of a sample rate, atime period for sampling, or a spectral bandwidth over which to samplesuch that a predetermined data transmission rate can be maintained whentransmitting the sampled data.
 10. The method of claim 1, wherein thedynamically changing transmission characteristic uses the availablechannel bandwidth parameter to determine the spectral bandwidth as abandwidth over which to measure data.
 11. The method of claim 1, whereinthe available channel bandwidth parameter includes a spectral targetband, and wherein the spectral bandwidth is chosen for the dynamicallychanging transmission characteristic to include at least a part of thespectral target band.
 12. The method of claim 1, wherein the dynamicallychanging transmission characteristic uses the available channelbandwidth parameter to determine the time period as a time period overwhich to measure data.
 13. The method of claim 1, wherein the availablechannel bandwidth parameter includes a target time period, and whereinthe time period for the dynamically changing transmission characteristicis chosen to include at least a part of the target time period.
 14. Themethod of claim 1, wherein when the dynamically changing transmissioncharacteristic includes a second sample rate, updating the samplingoperation includes changing a first sample rate of the samplingoperation to be the second sample rate.
 15. The method of claim 1,wherein measuring signal energy at a location of the sensor measuresspecific bandwidths or frequencies, wherein the specific bandwidths orfrequencies are chosen based on a signal of interest.
 16. The method ofclaim 1, wherein measuring signal energy is performed over a timeperiod, such as the time period in the sampling operation updated. 17.The method of claim 1, wherein the method is performed repeatedly by thesensor to dynamically update the sampling operation over time to accountfor changes in a communications channel.
 18. The method of claim 17,wherein the changes in the communications channel are a result ofmovement of the sensor.
 19. A sensor for dynamically updating a samplingoperation, the sensor comprising: a sensing element; a data acquisitionunit; one or more processors; and one or more computer-readable mediahaving stored thereon instructions that are executable by the one ormore processors to configure the sensor to dynamically update a samplingoperation using the sensing element, including instructions that areexecutable to configure the sensor to perform at least the following:obtain a dynamically changing transmission characteristic based on anavailable channel bandwidth parameter, the dynamically changingtransmission characteristic comprising at least one of a sample rate, atime period, or a spectral bandwidth; update the sampling operation ofthe sensor; gather data using the updated sampling operation at the dataacquisition unit; and provide the data to a processing elementconfigured to analyze the data using a dynamically updatedcross-ambiguity function.
 20. A non-transitory computer-readable mediahaving stored thereon instructions that are executable by one or moreprocessors to dynamically modify a sampling operation of a sensor,including instructions that are executable to configure the sensor toperform at least the following: obtain a dynamically changingtransmission characteristic based on an available channel bandwidthparameter, the dynamically changing transmission characteristiccomprising at least one of a sample rate, a time period, or a spectralbandwidth; update the sampling operation of the sensor based on thetransmission characteristic; measure signal energy at a location of thesensor; sample the signal energy using the sampling operation to obtainsampled data; and provide the sampled data to a processing entityconfigured to analyze the data using a dynamically updatedcross-ambiguity function.